An IoT Based Solution for Cyber-Physical Fusion in Shop-Floor

  • Ji-hong YanEmail author
  • Zi-min Fu
  • Ming-yang Zhang
  • Yan-ling Zhang
Conference paper


Smart manufacturing plays an important role in the transformation and upgrading of manufacturing industry and the China Manufacturing 2025 Strategy. And the cyber-physical fusion is a critical process to achieve the interconnection and interoperability between the cyber and physical world of manufacturing. Combing with IoT, a solution to realize cyber-physical fusion for heterogeneous objects in shop-floor is presented. The architecture and key technologies of the solution are investigated. Then a remote management platform is implemented. Logistics tracking, production visualization, equipment interconnection and remote operation are realized and can be remotely accessed by portable terminals via Internet. The proposed solution is verified by the actual machining and assembly workshop in a laboratory at Harbin Institute of Technology.


Cyber model Cyber-physical fusion Cyber physical systems Equipment interconnection Internet of things Radio frequency identification 



This work is funded by NSFC-NSF (Grant No. 51561125002).


  1. 1.
    B. Chu, W.J. Tolone, J. Long, W.J. Tolone, R. Wilhelm, Y. Peng et al., Towards intelligent integrated manufacturing planning-execution. Int. J. Agil. Manuf. (in press)Google Scholar
  2. 2.
    J. Fu, Development status and trend of intelligent manufacturing equipment (in Chinese). J. Mech. Electr. Eng. 31(08), 959–962 (2014)Google Scholar
  3. 3.
    E.A. Lee, Cyber physical systems: design challenges, in 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (ISORC) (IEEE Computer Society, Orlando, FL, USA, 2008), pp. 363–369Google Scholar
  4. 4.
    J. Lee, B. Bagheri, H.A. Kao, A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manuf. Lett. 3, 18–23 (2015)CrossRefGoogle Scholar
  5. 5.
    F. Tao, W. Liu, J. Liu, X. Liu, Q. Liu, T. Qu et al., Digital twin and its potential application exploration (in Chinese). Comput. Integr. Manuf. Syst. 24(1), 1–18 (2018)Google Scholar
  6. 6.
    R. Want, An introduction to RFID technology. IEEE Pervasive Comput. 5(1), 25–33 (2006)CrossRefGoogle Scholar
  7. 7.
    H. Yang, L. Yang, S.H. Yang, Hybrid Zigbee RFID sensor network for humanitarian logistics centre management. J. Netw. Comput. Appl. 34(3), 938–948 (2011)CrossRefGoogle Scholar
  8. 8.
    Y. Zhang, G. Zhang, J. Wang, Real-time information capturing and integration framework of the internet of manufacturing things. Int. J. Comput. Integr. Manuf. 28(8), 811–822 (2015)CrossRefGoogle Scholar
  9. 9.
    C. Hein, T. Ritter, M. Wagner, Model-driven tool integration with ModelBus, in Workshop Future Trends of Model-Driven Development (2009), pp. 50–52Google Scholar
  10. 10.
    S. Kalpakjian, S.R. Schmid, Manufacturing Engineering and Technology (Pearson, Upper Saddle River, NJ, USA, 2014), pp. 468–476Google Scholar
  11. 11.
    R.Y. Zhong, Q. Dai, T. Qu, RFID-enabled real-time manufacturing execution system for mass-customization production. Robot. Comput.-Integr. Manuf. 29(2), 283–292 (2013)CrossRefGoogle Scholar
  12. 12.
    X. Wu, Y. Wang, J. Bai, H. Wang, C. Chu, RFID application challenges and risk analysis, in 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management (IE&EM) (IEEE, 2010), pp. 1086–1090Google Scholar
  13. 13.
    H. Christian, C. Weigand, J. Bernhard, Wireless medical sensor network with ZigBee, in Proceedings of the 5th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications, Madrid, Spain, 15–17 February 2006, pp. 12–15Google Scholar
  14. 14.
    I. Orovic, M. Orlandic, S. Stankovic, Z. Uskokovic, A virtual instrument for time-frequency analysis of signals with highly nonstationary instantaneous frequency. IEEE Trans. Instrum. Meas. 60(3), 791–803 (2011)CrossRefGoogle Scholar
  15. 15.
    C. Elliott, V. Vijayakumar, W. Zink, R. Hansen, National Instruments LabVIEW: A programming environment for laboratory automation and measurement. J. Assoc. Lab. Autom. 12(1), 17–24 (2007)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Ji-hong Yan
    • 1
    Email author
  • Zi-min Fu
    • 1
  • Ming-yang Zhang
    • 1
  • Yan-ling Zhang
    • 1
  1. 1.Department of Industrial EngineeringHarbin Institute of TechnologyHarbinChina

Personalised recommendations